| 基于遥感信息融合的阜新煤矿排土场地物提取与分类 |
| |
| 引用本文： | 韩云霞,李民赞,孙 红,李道亮.基于遥感信息融合的阜新煤矿排土场地物提取与分类[J].农业工程学报,2009,25(13):277-282. |
| |
| 作者姓名： | 韩云霞 李民赞 孙 红 李道亮 |
| |
| 作者单位： | 中国农业大学现代精细农业系统集成教育部重点实验室，北京 100083;中国农业大学现代精细农业系统集成教育部重点实验室，北京 100083;中国农业大学现代精细农业系统集成教育部重点实验室，北京 100083;中国农业大学现代精细农业系统集成教育部重点实验室，北京 100083 |
| |
| 基金项目： | 科技部国际合作重点项目（2007DFA91050）；863计划（2006AA10Z202） |
| |
| 摘 要： | 结合地面测试高光谱数据及卫星遥感数据，对矿区地物信息进行提取，可有助于快速获取矿区地表信息，为矿区废弃地植被恢复提供辅助决策信息支持具有重要意义。该文以阜新市海州矿区排土场为研究对象，对不同波段组合的SPOT-5遥感影像进行了分类方法和分类精度评价研究。结果表明：排土场影像在波段组合与融合之后进行分类，分类精度提高不明显；而通过组合SPOT多光谱影像和植被指数图像，并结合地面测试的高光谱特征曲线建立分类模板，可以有效地提高地物分类精度，总体分类精度为85.48%，Kappa系数为0.8197。分类结果满足对排土场地物调查的实际需要，为建立排土场植被恢复等级提供了数据基础。
|
| 关 键 词： | 遥感，分类，精度，地物信息提取，排土场，植被指数 |
| 收稿时间： | 2009/6/30 0:00:00 |
| 修稿时间： | 2009/9/11 0:00:00 |
Feature extraction and classification of coal mine overburden dumps based on data merging of multi-source remote sensing |
| |
| Han Yunxi,Li Minzan,Sun Hong and Li Daoliang.Feature extraction and classification of coal mine overburden dumps based on data merging of multi-source remote sensing[J].Transactions of the Chinese Society of Agricultural Engineering,2009,25(13):277-282. |
| |
| Authors: | Han Yunxi Li Minzan Sun Hong and Li Daoliang |
| |
| Institution: | Key Laboratory of Modern Precision Agriculture System Integration Research Ministry of Education, China Agricultural University, Beijing 100083, China,Key Laboratory of Modern Precision Agriculture System Integration Research Ministry of Education, China Agricultural University, Beijing 100083, China,Key Laboratory of Modern Precision Agriculture System Integration Research Ministry of Education, China Agricultural University, Beijing 100083, China and Key Laboratory of Modern Precision Agriculture System Integration Research Ministry of Education, China Agricultural University, Beijing 100083, China |
| |
| Abstract: | Feature extraction of coal mine using hyperspectral data remote sensing (RS) images was help for decision-making of revegetation and could provide technology reference for further researches. Object spectral characteristics of coal mine overburden dumps were quantitatively analyzed and classified based on multi-source remote sensing data. The hyper-spectral data were collected and the surface soil and vegetation were measured in Fuxin opencast coal overburden dumps. According to the analysis of remote sensing images, different bands images of SPOT-5 were used to classify the surface objects. The results indicated that the classification accuracy was not improved obviously using bands combination and merging. However, the evaluation accuracy can be improved effectively by combining four SPOT5 multi-spectral images, four vegetation index (VI) images and the hyper-spectral characteristics curves of the ground objectives, which achieved the total accuracy 85.48% and Kappa coefficient 0.8197. The results satisfied the needs of the objects investigation of overburden dump and provided the references for gradation of revegetaion. |
| |
| Keywords: | remote sensing classification feature extraction accuracy vegetation index |
|
| 点击此处可从《农业工程学报》浏览原始摘要信息 |
| 点击此处可从《农业工程学报》下载免费的PDF全文 |
|
